Estimating fetal and maternal genetic contributions to premature birth from multiparous pregnancy histories of twins using MCMC and maximum-likelihood approaches.
Estimating fetal and maternal genetic contributions to premature birth from multiparous pregnancy histories of twins using MCMC and maximum-likelihood approaches.
复制标题
DOI：
10.1375/twin.12.4.333
复制
发表时间：
2009-08
期刊：
影响因子：
--
通讯作者：
Eaves LJ
中科院分区：
文献类型：
--
作者：
York TP;Strauss JF 3rd;Neale MC;Eaves LJ
遗传和环境因素对早产的影响在家族研究中并不简单，因为病因可能涉及母体和胎儿基因。马尔可夫链蒙特卡罗（MCMC）方法是一种灵活的方法，用于定义用户指定的协方差结构，以处理多个随机效应和分层依赖性固有的双胞胎（COT）研究的妊娠结局。所提出的方法很容易修改，以允许将胎龄作为连续特征和反映是否存在早产的二元结果进行研究。估计胎儿和母体的遗传因素和环境的影响证明使用MCMC方法在WinBUGS和最大似然法在弗吉尼亚州COT样本，包括7,061出生。总之，虽然母亲和胎儿的遗传因素的贡献得到了支持，使用两个结果，额外的出生和/或扩展的关系，需要同时精确地估计两个遗传效应。我们预计MCMC方法的灵活性，以处理越来越复杂的模型是特别相关的出生结果的研究。
The analysis of genetic and environmental contributions to preterm birth is not straightforward in family studies, as etiology could involve both maternal and fetal genes. Markov Chain Monte Carlo (MCMC) methods are presented as a flexible approach for defining user-specified covariance structures to handle multiple random effects and hierarchical dependencies inherent in children of twin (COT) studies of pregnancy outcomes. The proposed method is easily modified to allow for the study of gestational age as a continuous trait and as a binary outcome reflecting the presence or absence of preterm birth. Estimation of fetal and maternal genetic factors and the effect of the environment are demonstrated using MCMC methods implemented in WinBUGS and maximum likelihood methods in a Virginia COT sample comprising 7,061 births. In summary, although the contribution of maternal and fetal genetic factors was supported using both outcomes, additional births and/or extended relationships are required to precisely estimate both genetic effects simultaneously. We anticipate the flexibility of MCMC methods to handle increasingly complex models to be of particular relevance for the study of birth outcomes.
登录
查看更多内容
影响因子：
2.6
作者：
Eaves, L;Erkanli, A
通讯作者：
Erkanli, A
影响因子：
2.6
作者：
Eaves, L;Erkanli, A;Foley, D
通讯作者：
Foley, D
DOI：
10.1111/j.1469-7610.2008.01956.x
发表时间：
2008-11-01
影响因子：
7.6
作者：
Eaves, Lindon J.;Silberg, Judy L.
通讯作者：
Silberg, Judy L.
DOI：
10.1080/19485565.1973.9988053
发表时间：
1973-01-01
期刊：
SOCIAL BIOLOGY
影响因子：
--
作者：
FULKER, DW
通讯作者：
FULKER, DW
影响因子：
3.8
作者：
HALEY, CS;JINKS, JL;LAST, K
通讯作者：
LAST, K